From d935d30e4cbb1714a70ebee8eeb79607d0ffcb72 Mon Sep 17 00:00:00 2001
From: tsukumi <tsukumijima@users.noreply.github.com>
Date: Mon, 23 Sep 2024 21:07:27 +0900
Subject: [PATCH] Add: test code for CoreMLExecutionProvider on a trial basis
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Currently ONNXRuntime's CoreML support is not very good, and on my environment, I get errors like “coreml_execution_provider.cc:192 operator() Input (/sdp/flows.3/GatherND_2_output_0) has a dynamic shape ({-1,-1}) but the runtime shape ({0,10}) has zero elements. This is not supported by the CoreML EP.” and inference fails.
I hope this will be fixed in a future version of ONNXRuntime, and leave the test code as it is.
---
 .gitignore                         | 2 ++
 pyproject.toml                     | 2 ++
 style_bert_vits2/utils/__init__.py | 6 ++++--
 tests/test_main.py                 | 9 +++++++++
 4 files changed, 17 insertions(+), 2 deletions(-)

diff --git a/.gitignore b/.gitignore
index 9e2934f..f239417 100644
--- a/.gitignore
+++ b/.gitignore
@@ -5,6 +5,8 @@ dist/
 .coverage*
 .ipynb_checkpoints/
 .ruff_cache/
+.DS_Store
+._*
 
 /*.yml
 !/default_config.yml
diff --git a/pyproject.toml b/pyproject.toml
index 7ba547f..3b20d05 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -109,6 +109,8 @@ test = "pytest -s tests/test_main.py::test_synthesize_onnx_cpu"
 test-cuda = "pytest -s tests/test_main.py::test_synthesize_onnx_cuda"
 # Usage: `hatch run test-onnx:test-directml`
 test-directml = "pytest -s tests/test_main.py::test_synthesize_onnx_directml"
+# Usage: `hatch run test-onnx:test-coreml`
+test-coreml = "pytest -s tests/test_main.py::test_synthesize_onnx_coreml"
 # Usage: `hatch run test-onnx:coverage`
 test-cov = "coverage run -m pytest -s tests/test_main.py::test_synthesize_onnx_cpu"
 # Usage: `hatch run test-onnx:cov-report`
diff --git a/style_bert_vits2/utils/__init__.py b/style_bert_vits2/utils/__init__.py
index d86b476..9d43784 100644
--- a/style_bert_vits2/utils/__init__.py
+++ b/style_bert_vits2/utils/__init__.py
@@ -5,10 +5,12 @@ def torch_device_to_onnx_providers(
     device: str,
 ) -> Sequence[Union[str, tuple[str, dict[str, Any]]]]:
     if device.startswith("cuda"):
-        # cudnn_conv_algo_search を DEFAULT にすると推論速度が大幅に向上する
-        # ref: https://medium.com/neuml/debug-onnx-gpu-performance-c9290fe07459
         return [
+            # cudnn_conv_algo_search を DEFAULT にすると推論速度が大幅に向上する
+            # ref: https://medium.com/neuml/debug-onnx-gpu-performance-c9290fe07459
             ("CUDAExecutionProvider", {"cudnn_conv_algo_search": "DEFAULT"}),
+            # CUDA が利用できない場合、可能であれば DirectML を利用する
+            ("DmlExecutionProvider", {"device_id": 0}),
             ("CPUExecutionProvider", {}),
         ]
     else:
diff --git a/tests/test_main.py b/tests/test_main.py
index 5126232..d50b502 100644
--- a/tests/test_main.py
+++ b/tests/test_main.py
@@ -125,3 +125,12 @@ def test_synthesize_onnx_directml():
             ("DmlExecutionProvider", {"device_id": 0}),
         ],
     )
+
+
+def test_synthesize_onnx_coreml():
+    synthesize(
+        inference_type="onnx",
+        onnx_providers=[
+            ("CoreMLExecutionProvider", {}),
+        ],
+    )